songsee

Generate spectrograms, mel spectrograms, and chromagrams from audio files.

2|1|Updated May 10, 2026

Search Tags:#visualization #signal processing #audio #spectrogram #music analysis #audio features

Ready to run

npx skills add https://github.com/zli5460/hermes-agent-X-Phoenix-Architecture --skill songsee-zli5460

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: songsee
Source: https://github.com/zli5460/hermes-agent-X-Phoenix-Architecture/tree/main/skills/media/songsee
Command: npx skills add https://github.com/zli5460/hermes-agent-X-Phoenix-Architecture --skill songsee-zli5460

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

It enables users to generate comprehensive visual representations of audio signals, facilitating analysis and understanding of sound characteristics.

Core Features & Use Cases

Audio Visualization: Produce spectrograms, mel spectrograms, chromagrams, and other visual features from audio files.
Music and Audio Analysis: Assist with genre classification, instrument detection, audio quality assessment, and research by visualizing audio features.
Use Case: A researcher can quickly visualize the spectral content of a song to analyze its structure or compare different recordings. Simply invoke the command with the desired audio file and visualization types to generate insights.

Quick Start

Generate a spectrogram from an audio file named 'sound.mp3' and save it as an image file.

Frequently Asked Questions about songsee

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate an audio spectrogram from an mp3 file?▼

You can generate a spectrogram from an mp3 file by invoking the visualization command with the target audio file. The tool processes the sound file to produce a visual image representing its spectral content for analysis.

What types of audio feature visualizations can I create for music analysis?▼

For music analysis, you can create spectrograms, mel spectrograms, and chromagrams. These visual features assist in examining genre classification, instrument detection, and audio quality assessment for research tasks.

Do I need ffmpeg to process audio files for signal visualization?▼

Ffmpeg is optionally used for audio processing during signal visualization. The tool also supports processing via Go libraries, allowing you to generate visual representations of audio data without strict dependencies.

Can I use this tool for audio quality assessment and research?▼

Yes, you can use this tool for audio quality assessment and research. It aids researchers by visualizing audio features, enabling quick comparison of different recordings and detailed examination of sound structure.

What is the best way to visualize the spectral content of a song?▼

The best way to visualize the spectral content of a song is by generating a spectrogram. This visual representation maps the audio frequencies over time, facilitating quick insights into the music's signal processing characteristics.